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@article{1691217,
author = {Husák, Martin and Žádník, Martin and Bartoš, Václav and Sokol, Pavol},
article_number = {December},
doi = {http://dx.doi.org/10.1016/j.dib.2020.106530},
keywords = {Cyber security;Intrusion detection alerts;Information exchange;Geolocation;Reputation},
language = {eng},
issn = {2352-3409},
journal = {Data in Brief},
title = {Dataset of intrusion detection alerts from a sharing platform},
url = {https://doi.org/10.1016/j.dib.2020.106530},
volume = {33},
year = {2020}
}
TY - JOUR
ID - 1691217
AU - Husák, Martin - Žádník, Martin - Bartoš, Václav - Sokol, Pavol
PY - 2020
TI - Dataset of intrusion detection alerts from a sharing platform
JF - Data in Brief
VL - 33
IS - December
SP - 1-12
EP - 1-12
PB - Elsevier
SN - 23523409
KW - Cyber security;Intrusion detection alerts;Information exchange;Geolocation;Reputation
UR - https://doi.org/10.1016/j.dib.2020.106530
N2 - The dataset contains intrusion detection alerts obtained via an alert sharing platform (SABU) for one week. A plethora of heterogeneous intrusion detection systems deployed across several organizations contributed to the sharing platform. The alerts are stored in the intrusion Detection Extensible Alert (IDEA) format and categorized using the eCSIRT.net Incident Taxonomy. Dataset can be used in several areas of cybersecurity research for the analysis of intrusion detection alerts including temporal and spatial correlations, reputation scoring, attack scenario reconstruction, and attack projection. The network identifiers (e.g., IP addresses, hostnames) are anonymized. However, the list of interesting features (e.g., presence on blacklists, geolocation) of such entities at the time of data collection is provided.
ER -
HUSÁK, Martin, Martin ŽÁDNÍK, Václav BARTOŠ and Pavol SOKOL. Dataset of intrusion detection alerts from a sharing platform. \textit{Data in Brief}. Elsevier, 2020, vol.~33, December, p.~1-12. ISSN~2352-3409. Available from: https://dx.doi.org/10.1016/j.dib.2020.106530.
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